
Biomechanics Principles and Applications - Schneck and Bronzino
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Biomechanics: Principles and Applications |
FIGURE 7.2 (a) Injury severity from blunt impact of human cadavers as a function of the maximum chest compression. (From Viano [1988], with permission.) (b) Severity of skeletal injury and incidence of internal organ injury as a function of maximum chest compression for blunt impacts of human cadavers. (From Viano [1988]. With permission.)
the maximum compression of the chest, as measured by the percentage change in the anteroposterior thickness of the body. A relationship between injury risk and compression involves energy stored by elastic deformation of the body. Stored energy Es by a spring representing the ribcage and soft tissues is related to the displacement integral of force: Es = ∫F dx. Force in a spring is proportional to deformation: F = kx, where k is a spring constant. Stored energy is Es = k∫x dx = 0.5kx2. Over a reasonable range, stored energy is proportional to deformation or compression, so Es ≈ C.
Tests with human volunteers showed that compression up to 20% during moderate-duration loading was fully reversible. Cadaver impacts with compression greater than 20% (Fig. 7.2a) an increase in rib fractures and internal organ injury as the compression increased to 40%. The deflection tolerance was originally set at 8.8 cm (3.5 in) for moderate but recoverable injury. This represents 39% compression. However, at this level of compression, multiple rib fractures and serious injury can occur, so a more conservative tolerance of 34% is used to avert the possibility of flail chest (Fig. 7.2b). This reduces the risk of direct loading on the heart, lungs, and internal organs by a loss of the protective function of the ribcage.
Viscous Injury
The velocity of body deformation is an important factor in impact injury. For example, when a fluidfilled organ is compressed slowly, energy can be absorbed by tissue deformation without damage. When loaded rapidly, the organ cannot deform fast enough, and rupture may occur without significant change in shape, even though the load is substantially higher than for the slow-loading condition.
The viscoelastic behavior of soft tissues is important when the velocity of deformation exceeds 3 m/s. For lower speeds, such as in slow crushing loads or for a belt-restrained occupant in a frontal crash, tissue compression is limited by elastic properties resisting skeletal and internal organ injury. For higher speeds of deformation, such as occupant loading by the door in a side impact or for an unrestrained occupant or pedestrian, maximum compression does not adequately address the viscous and inertial properties of the torso, nor the time of greatest injury risk. In these conditions, the tolerance to compression is progressively lower as the speed of deformation increases, and the velocity of deformation becomes a dominant factor in injury.
Insight on a rate-dependent injury mechanism came from over 20 years of research by Clemedson and Jonsson [1979] on high-speed impact and blast-wave exposures. The studies confirmed that tolerable compression inversely varied with the velocity of impact. The concept was studied further in relation to

Biomechanics of Chest and Abdomen Impact |
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the abdomen by Lau [1981] for frontal impacts in the range of 5 to 20 m/s (10 to 45 mi/h). The liver was the target organ. Using a maximum compression of 16%, the severity of injury increased with the speed of loading, including serious mutilation of the lobes and major vessels in the highest-speed impacts. While the compression was within limits of volunteer loading at low speeds, the exposure produced critical injury at higher speeds. Subsequent tests on other animals and target organs verified an interrelationship between body compression, deformation velocity, and injury.
The previous observations led Viano and Lau [1988] to propose a viscous injury mechanism for soft biologic tissues. The viscous response VC is defined as the product of velocity of deformation V and compression C, which is a time-varying function in an impact. The parameter has physical meaning to absorbed energy Ea by a viscous dashpot under impact loading. Absorbed energy is related to the displacement integral of force: Ea = ∫F dx, and force in a dashpot is proportional to the velocity of deformation: F = cV, where c is a dashpot parameter. Absorbed energy is Ea = c∫V dx, or a time integral by substitution: Ea = c∫V2 dt. The integrand is composed of two responses, so Ea = c[∫d(Vx) – ∫ax dt], where a is acceleration across the dashpot. The first term is the viscous response, and the second is an inertial term related to the deceleration of fluid set in motion. Absorbed energy is given by Ea = c(Vx – ∫ax dt). The viscous response is proportional to absorbed energy, or Ea ≈ VC, during the rapid phase of impact loading prior to peak compression.
Subsequent tests by Lau and Viano [1988, 1986] verified that serious injury occurred at the time of peak VC. For blunt chest impact, peak VC occurs in about half the time for maximum compression. Rib fractures also occur progressively with chest compression, as early as 9 to 14 ms—at peak VC—in a cadaver impact requiring 30 ms to reach peak compression. Upper abdominal injury by steering wheel contact also relates to viscous loading. Lau [1987] showed that limiting the viscous response by a selfaligning steering wheel reduced the risk of liver injury, as does force limiting an armrest in side impacts. Animal tests also have shown that VC is a good predictor of functional injury to the heart and respiratory systems. In these experiments, Stein [1982] found that the severity of cardiac arrhythmia and traumatic apnea was related to VC. This situation is important to baseball impact protection of children [Viano et al., 1992] and in the design of bulletproof protective vests [Quatros, 1994].
Figure 7.3 summarizes injury mechanisms associated with impact deformation. For low speeds of deformation, the limiting factor is crush injury from compression C of the body. This occurs at C = 35 to 40% depending on the contact area and orientation of loading. For deformation speeds above 3 m/s,
FIGURE 7.3 Biomechanics of chest injury by a crushing injury mechanism limited by tolerable compression at Cmax = 35%, a viscous injury mechanism limited by the product of velocity and extent of deformation at VCmax = 1.0 m/s, and a blast injury mechanism for shock-wave loading.

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injury is related to peak viscous response of VC = 1.0 m/s. In a particular situation, injury can occur by a compression or viscous responses, or both, since these responses occur at different times in an impact. At extreme rates of loading, such as in a blast-wave exposure, injury occurs with less than 10 to 15% compression by high energy transfer to viscous elements of the body.
7.3 Biomechanical Responses during Impact
The reaction force developed by the chest varies with the velocity of deformation and biomechanics is best characterized by a family of force-deflection responses. Figure 7.4 summarizes frontal and lateral chest biomechanics for various impact speeds. The dynamic compliance is related to viscous, inertial, and elastic properties of the body. The initial rise in force is due to inertia as the sternal mass is rapidly accelerated to the impact speed. The plateau force is related to the viscous component, which is rate dependent, and a superimposed elastic stiffness that increases force with chest compression. Unloading provides a hysteresis loop representing the energy absorbed by body deformation.
Melvin [1988] analyzed frontal biomechanics and modeled the force-deflection response as an initial stiffness A = 0.26 + 0.60(V – 1.3) and a plateau force B = 1.0 + 0.75(V – 3.7), where A is in kN/cm, B is in kN, and V is in m/s. The force B reasonably approximates the plateau level for lateral chest and abdominal impacts, but the initial stiffness is considerably lower at A = 0.12(V – 1.2) for side loadings.
A simple, but relevant, lumped-mass model of the chest was developed by Lobdell [1973] and is shown in Fig. 7.5. The impacting mass is m1, and skin compliance is represented by k12. An energy-absorbing
FIGURE 7.4 Frontal and lateral force-deflection response of the human cadaver chest at various speeds of blunt pendulum impact. The initial stiffness is followed by a plateau force until unloading. (From Kroell [1974] and Viano [1989], summarized by Cavanaugh [1993]. With permission.)

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FIGURE 7.4 (continued)
interface was added by Viano [1987] to evaluate protective padding. Chest structure is represented by a parallel Voigt and Maxwell spring-dashpot system that couples the sternal m2 and spinal m3 masses. When subjected to a blunt sternal impact, the model follows established force-deflection corridors. The biomechanical model is effective in studying compression and viscous responses. It also simulates military exposure to high-speed nonpenetrating projectiles (Fig. 7.6), even though the loading conditions are quite different from the cadaver database used to develop the model. This mechanical system characterizes the elastic, viscous, and inertial components of the torso.

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FIGURE 7.5 Lumped-mass model of the human thorax with impacting mass and energy-absorbing material interface. The biomechanical parameters are given for mass, spring, and damping characteristics of the chest in blunt frontal impact. (Modified from Lobdell [1973] by Viano [1987]. With permission.)
FIGURE 7.6 Tolerance levels for blunt loading as a function of impact mass and velocity. The plot includes information from automotive impact situations and from high-speed military projectile impacts. The Lobdell model is effective over the entire range of impact conditions. (Modified from Quatros [1993]. With permission.)

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The Hybrid III dummy reported on by Foster [1977] was the first to demonstrate human-like chest responses typical of the biomechanical data for frontal impacts. Rouhana [1989] developed a frangible abdomen, useful in predicting injury for lap-belt submarining. More recent work by Schneider [1992] led to a new prototype frontal dummy. Lateral impact tests of cadavers against a rigid wall and blunt pendulum led to side-impact dummies such as the Eurosid and Biosid [Mertz, 1993].
7.4 Injury Risk Assessment
Over years of study, tolerances have been established for most responses of the chest and abdomen. Table 7.1 provides tolerance levels from reviews by Cavanaugh [1993] and Rouhana [1993]. While these are single thresholds, they are commonly used to evaluate safety systems. The implication is that for biomechanical responses below tolerance there is no injury, and for responses above tolerance there is injury. An additional factor is biomechanical response scaling for individuals of different size and weight. The commonly accepted procedure involves equal stress and velocity, which enabled Mertz et al. [1989] to predict injury tolerances and biomechanical responses for different-sized adult dummies.
Injury risk assessment is frequently used. It evaluates the probability of injury as a continuous function of a biomechanical response. A logist function relates injury probability p to a biomechanical response x by p(x) = [1 + exp(α – βx)]–1, where α and β are parameters derived from statistical analysis of biomechanical data. This function provides a sigmoidal relationship with three distinct regions in Fig. 7.7. For low biomechanical response levels, there is a low probability of injury. Similarly, for very high levels, the risk asymptotes to 100%. The transition region between the two extremes involves risk that is proportional to the biomechanical response. A sigmoidal function is typical of human tolerance because it represents the distribution in weak through strong subjects in a population exposed to impact. Table 7.2 summarizes available parameters for chest and abdominal injury risk assessment.
TABLE 7.1 Human Tolerance for Chest and Abdomen Impact
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Chest |
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Abdomen |
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Criteria |
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Frontal |
Lateral |
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Frontal |
Lateral |
Criteria |
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Acceleration |
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Acceleration |
3-ms limit |
60 g |
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TTI |
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85–90 g |
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ASA |
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30 g |
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AIS 4+ |
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45 g |
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39 g |
AIS 4+ |
Force |
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Force |
Sternum |
3.3 kN |
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Chest + shoulder |
8.8 kN |
10.2 kN |
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AIS 3+ |
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2.9 kN |
3.1 kN |
AIS 3+ |
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AIS 4+ |
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5.5 kN |
3.9 kN |
6.7 kN |
AIS 4+ |
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Pressure |
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Pressure |
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166 kPa |
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AIS 3+ |
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216 kPa |
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AIS 4+ |
Compression |
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Compression |
Rib fracture |
20% |
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Ribcage |
32% |
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38% |
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AIS 3+ |
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Flail chest |
40% |
38% |
48% |
44% |
AIS 4+ |
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Viscous |
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Viscous |
AIS 3+ |
1.0 m/s |
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AIS 3+ |
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AIS 4+ |
1.3 m/s |
1.47 m/s |
1.4 m/s |
1.98 m/s |
AIS 4+ |
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Source: Adapted from Cavanaugh [1993] and Rouhana [1993].

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FIGURE 7.7 Typical logist injury-probability function relating the risk of serious injury to the viscous response of the chest. (From Viano [1988]. With permission.)
TABLE 7.2 Injury Probability Functions for Blunt Impact
Body Region |
ED25% |
α |
β |
X2 |
p |
R |
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Frontal Impact |
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Chest (AIS 4+) |
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VC |
1.0 m/s |
11.42 |
11.56 |
25.6 |
0.000 |
0.68 |
C |
34% |
10.49 |
0.277 |
15.9 |
0.000 |
0.52 |
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Lateral Impact |
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Chest (AIS 4+) |
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VC |
1.5 m/s |
10.02 |
6.08 |
13.7 |
0.000 |
0.77 |
C |
38% |
31.22 |
0.79 |
13.5 |
0.000 |
0.76 |
Abdomen (AIS 4+) |
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VC |
2.0 m/s |
8.64 |
3.81 |
6.1 |
0.013 |
0.60 |
C |
47% |
16.29 |
0.35 |
4.6 |
0.032 |
0.48 |
Pelvis (pubic ramus fracture) |
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C |
27% |
84.02 |
3.07 |
11.5 |
0.001 |
0.91 |
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Source: Adapted from Viano [1989]. With permission.
References
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Cavanaugh JM, Zhu Y, Huang Y et al. 1993. Injury and response of the thorax in side impact cadaveric tests. In Proceedings of the 37th Stapp Car Crash Conference, pp. 199–222, SAE Paper no. 933127. Warrendale, PA, Society of Automotive Engineers.
Eiband AM. 1959. Human Tolerance to Rapidly Applied Acceleration: A Survey of the Literature, NASA Memo No. 5-19-59E. Washington, D.C., National Aeronautics and Space Administration.
Foster JK, Kortge JO, Wolanin MJ. 1977. Hybrid III—a biomechanically-based crash test dummy. In
Proceedings of the 21st Stapp Car Crash Conference, pp. 975–1014, SAE Paper no. 770938. Warrendale, PA, Society of Automotive Engineers.

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Gadd CW, Patrick LM. 1968. Systems versus Laboratory Impact Tests for Estimating Injury Hazards, SAE Paper no. 680053. Warrendale, PA, Society of Automotive Engineers.
Jonsson A, Clemedson CJ et al. 1979. Dynamic factors influencing the production of lung injury in rabbits subjected to blunt chest wall impact. Aviat Space Environ Med 50:325.
King Al. 1984. Regional tolerance to impact acceleration. In SP-622. Warrendale, PA, Society of Automotive Engineers.
Kroell CK, Schneider DC, Nahum AM. 1971. Impact tolerance and response to the human thorax. In
Proceedings of the 15th Stapp Car Crash Conference, pp. 84–134, SAE Paper no. 710851. Warrendale, PA, Society of Automotive Engineers.
Kroell CK, Schneider DC, Nahum AM. 1974. Impact tolerance and response to the human thorax II. In
Proceedings of the 18th Stapp Car Crash Conference, pp. 383–457, SAE Paper no. 741187. Warrendale, PA, Society of Automotive Engineers.
Lau IV, Viano DC. 1981. Influence of impact velocity on the severity of nonpenetrating hepatic injury. Trauma 21(2):115.
Lau IV, Viano DC. 1986. The viscous criterion—bases and application of an injury severity index for soft tissue. In Proceedings of the 30th Stapp Car Crash Conference, pp. 123–142, SAE Paper no. 861882. Warrendale, PA, Society of Automotive Engineers.
Lau IV, Viano DC. 1988. How and when blunt injury occurs: implications to frontal and side impact protection. In Proceedings of the 32nd Stapp Car Crash Conference, pp. 81–100, SAE Paper no. 881714. Warrendale, PA, Society of Automotive Engineers.
Lau IV, Horsch JD, Andrzejak D et al. 1987. Biomechanics of liver injury by steering wheel loading. Trauma 27:225.
Lobdell TE, Kroell CK, Schneider DC et al. 1973. Impact response of the human thorax. In King WF, Mertz HJ (Eds.), Human Impact Response Measurement and Simulation, pp. 201–245. New York, Plenum Press.
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Melvin JW, King Al, Alem, NM. 1988. AATD system technical characteristics, design concepts, and trauma assessment criteria. AATD Task E-F Final Report, DOT-HS-807-224. Washington, D.C., U.S. Department of Transportation, National Highway Traffic Safety Administration.
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Mertz HJ, Irwin A, Melvin J et al. 1989. Size, Weight and Biomechanical Impact Response Requirements for Adult Size Small Female and Large Male Dummies, SAE Paper no. 890756. Warrendale, PA, Society of Automotive Engineers.
Morgan RM, Marcus JH, Eppinger RH. 1986. Side impact—the biofidelity of NHTSA’s proposed ATD and efficacy of TTI. In Proceedings of the 30th Stapp Car Crash Conference, pp. 27–40, SAE Paper no. 861877. Warrendale, PA, Society of Automotive Engineers.
Patrick LM, Kroell CK, Mertz HJ. 1965. Forces on the human body in simulated crashes. In Proceedings of the 9th Stapp Car Crash Conference, pp. 237–260. Warrendale, PA, Society of Automotive Engineers.
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Rouhana SW, Viano D, Jedrzejczak E et al. 1989. Assessing submarining and abdominal injury risk in the Hybrid III family of dummies. In Proceedings of the 33rd Stapp Car Crash Conference, pp. 257–279, SAE Paper no. 892440. Warrendale, PA, Society of Automotive Engineers.

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Rouhana SW. 1993. Biomechanics of abdominal trauma. In Nahum AM, Melvin JW (Eds.), Accidental Injury: Biomechanics and Prevention, pp. 391–428. New York, Springer-Verlag.
Schneider LW, Haffner MP et al. 1992. Development of an advanced ATD thorax for improved injury assessment in frontal crash environments. In Proceedings of the 36th Stapp Car Crash Conference, pp. 129–156, SAE Paper no. 922520. Warrendale, PA, Society of Automotive Engineers.
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Stalnaker RL, McElhaney JH, Roberts VL, Trollope ML. 1973. Human torso response to blunt trauma. In King WF, Mertz HJ (Eds.), Human Impact Response Measurement and Simulation, pp 181–199. New York, Plenum Press.
Stapp JP. 1970. Voluntary human tolerance levels. In Gurdjian ES, Lange WA, Patrick LM, Thomas LM (Eds.), Impact Injury and Crash Protection, pp. 308–349. Springfield, IL, Charles C Thomas.
Stein PD, Sabbah HN, Viano D et al. 1982. Response of the heart to nonpenetrating cardiac trauma. J Trauma 22(5):364.
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Viano DC. 1988. Cause and control of automotive trauma. Bull NY Acad Med 64:376.
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Roy B. Davis
Motion Analysis Laboratory Shriners Hospitals for Children
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Analysis of Gait
Peter A. DeLuca
Gait Analysis Laboratory |
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Connecticut Children’s |
8.1 |
Fundamental Concepts ...................................................... |
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Medical Center |
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Clinical Gait Analysis Information |
• Data Collection |
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Sylvia Õunpuu |
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Protocol • Measurement Approaches and Systems |
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8.2 |
Gait Data Reduction |
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Gait Analysis Laboratory |
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8.3 |
Illustrative Clinical Case |
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Connecticut Children’s |
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Medical Center |
8.4 |
Gait Analysis: Current Status............................................. |
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Gait analysis is the quantitative measurement and assessment of human locomotion including both walking and running. A number of different disciplines use gait analysis. Basic scientists seek a better understanding of the mechanisms that normal ambulators use to translate muscular contractions about articulating joints into functional accomplishment, e.g., level walking and stair climbing. Increasingly, researchers endeavor to better appreciate the relationship between the human motor control systems and gait dynamics. With respect to running, athletes and their coaches use gait analysis techniques in a ceaseless quest for meaningful improvements in performance while avoiding injury. Sports equipment manufacturers seek to quantify the perceived advantages of their products relative to a competitor’s offering.
In the realm of clinical gait analysis, medical professionals apply an evolving knowledge base in the interpretation of the walking patterns of impaired ambulators for the planning of treatment protocols, e.g., orthotic prescription and surgical intervention. Clinical gait analysis is an evaluation tool that allows the clinician to determine the extent to which an individual’s gait has been affected by an already diagnosed disorder [Brand and Crowninshield, 1981]. Examples of clinical pathologies currently served by gait analysis include amputation, cerebral palsy (CP), degenerative joint disease, poliomyelitis, multiple sclerosis, muscular dystrophy, myelodysplasia, rheumatoid arthritis, stroke, and traumatic brain injury.
Generally, gait analysis data collection protocols, measurement precision, and data reduction models have been developed to meet the requirements specific to the research, sport, or clinical setting. For example, gait measurement protocols in a research setting might include an extensive physical examination to characterize the anthropometrics of each subject. This time expenditure may not be possible in a clinical setting. Also, sport assessments generally require higher data acquisition rates because of increased velocity amplitudes relative to walking. The focus of this chapter is on the methods for the assessment of walking patterns of persons with locomotive impairment, i.e., clinical gait analysis. The discussion will include a description of the available measurement technology, the components of data collection and reduction, the type of gait information produced for clinical interpretation, and the strengths and limitations of clinical gait analysis.
8.1 Fundamental Concepts
Clinical Gait Analysis Information
Gait is a cyclic activity for which certain discrete events have been defined as significant. Typically, the gait cycle is defined as the period of time from the point of initial contact (also referred to as foot contact)
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